1. Technical Field
The disclosure relates to a technique of utterance verification.
2. Related Art
Speech recognition has a wide range of applications such as phone number inquiry systems, building access control systems, vehicle computer systems, voice control toys, and wireless communication devices that are the most popular in recent years. The most representative structure of the current speech recognition system is mainly based on a hidden Markov model (HMM). Although speech recognition provides such a wide range in applications, correctness of speech recognition hardly promotes the popularity thereof. Therefore, most researches on the speech recognition still focus on improvements of the correctness.
An utterance verification feature, an indispensable part of a speech recognition system, may effectively reject incorrect results of speech recognition caused by out-of-vocabulary voices or noises to improve correctness and reliability of the speech recognition. A commonly used technique is to perform utterance verification on a recognized vocabulary by using a Neural Network Model, garbage normalization, or N-best based confidence, etc.
However, the above utterance verification techniques require additional computations and sufficient memory space for storing models, or require to adjust a setting according to different environments. Therefore, it is needed to provide a method for utterance verification with a better effect and less computation and memory space.